Artificial Intelligence at Schlumberger

SCHLUMBERGER is a large, multinational corporation concerned primarily with the measurement, collection, and interpretation of data. For the past fifty years, most of its activities have been related to hydrocarbon exploration. The efficient location and production of hydrocarbons from an underground formation requires a great deal of knowledge about the formation, ranging in scale from the size and shape of the rock’s pore spaces to the size aud shape of the entire reservoir. Schlumberger provides its clients with two types of information: measurements, called logs, of the petrophysical properties of the rock around the borehole, such as its electrical, acoustical, and radioactive characteristics; and interpretations of these logs in terms of geophysical properties, such as porosity and mineral composition. Since log interpretation is an expert skill, the emergence of expert systems technology prompted Schlumberger’s initial interest in Artificial Intelligence. Our first, full-scale attempt at a commercial-quality expert system was the Dipmeter Advisor (Davis 1981; Gcrshman 1982; Smith 1983a). This system attempts to emulate human expert performance in the interpretation of subsurface geological features from measurements of the tilt of the underground layers. The program is written in INTERLISP-D and operates on the Xerox 1100 series Scientific Information Processor. It includes approximately 90 production rules, a forward-chaining inference engine, several feature detection algorithms, and a menu-driven graphical user interface. The Dipmeter Advisor system has recently begun to see service in some of Schlumberger’s Field Computation Centers. Following these initial efforts, Schlumbcrger has expanded its Artificial Intelligence activities, and is now engaged in both basic and applied research in a wide variety of areas: